Senior Staff Software Engineer, AI Platforms

pSemi Corporation, a Murata company, drives semiconductor integration by building on Peregrine Semiconductor’s 30-year legacy of technology advancements and a strong IP portfolio. With a focus on enhancing Murata’s world-class capabilities with high-performance semiconductors, pSemi’s product portfolio spans RF integration, power management, connected sensors, optical transceivers, antenna tuning, and RF frontends. These semiconductors enable advanced modules for smartphones, base stations, personal computers, electric vehicles, data centers, IoT devices, and healthcare.

About the role

As a Senior Staff Software Engineer focused on AI platforms, you will provide end-to-end technical leadership for the software systems that enable AI-assisted RFIC design and verification workflows. Your primary mandate will be to define and build the platform through which AI-enabled applications and intelligent agents safely interact with engineering tools, data, and computational infrastructure. This role centers on systems engineering, platform architecture, and productionalization rather than foundational model research or training. You will establish technical direction, convert emerging prototypes into dependable multi-user products, and create reusable platform capabilities supporting multiple engineering applications.

Responsibilities

• Own the architecture and evolution of distributed software platforms that support AI-enabled engineering workflows. Define service boundaries, APIs, data flows, execution models, asynchronous processing patterns, and platform standards reusable across multiple products and teams.
• Establish a multi-year technical direction while balancing near-term delivery, maintainability, security, and operational risk.
• Design and productionize systems incorporating generative AI, LLM services, intelligent agents, retrieval, tool-driven automation, and human approval workflows. Focus on reliability, evaluation, traceability, failure handling, policy enforcement, and secure execution.
• Create common patterns allowing new AI capabilities and engineering tools to be integrated efficiently and safely.
• Architect, implement, and maintain end-to-end software products spanning modern web applications, backend services, APIs, real-time interactions, and engineering integrations. Establish scalable design patterns for intuitive, maintainable, and reliable user experiences while remaining hands-on in critical codebase areas.
• Design, automate, and continuously improve development, testing, deployment, and production environments across AWS, Microsoft Azure, Google Cloud Platform, on-premises, or hybrid environments. Establish robust practices for containerization, Kubernetes, infrastructure as code, CI/CD, configuration management, release automation, networking, storage, and environment promotion.
• Lead the development of secure, resilient, and production-ready systems with strong observability, fault tolerance, recovery, and operational support. Define standards for identity and access management, authorization, secrets management, workload isolation, auditability, monitoring, incident response, root-cause analysis, and service-level objectives.
• Collaborate across software, infrastructure, AI, and RFIC engineering teams to automate workflows involving design, simulation, testbench configuration, job execution, data collection, analysis, verification, and report generation. Integrate AI-enabled capabilities with EDA tools in safe, reproducible, traceable, and engineer-friendly ways.
• Direct the design of data architectures and integration patterns connecting applications, databases, engineering tools, AI services, enterprise systems, and long-running computational workloads. Ensure data reliability, security, discoverability, and accessibility, and establish resilient orchestration patterns for queued, asynchronous, and failure-prone workflows.
• Serve as a technical authority across multiple products and engineering disciplines. Lead architectural reviews, resolve complex cross-system challenges, make build-versus-buy decisions, identify and retire systemic technical risk, establish engineering standards, and mentor other engineers.
• Independently investigate emerging software, cloud, AI platform, infrastructure, and developer-platform technologies. Identify practical opportunities to apply them within semiconductor engineering and produce clear architecture, design, operational, decision, and roadmap documentation.

Requirements

• Typically requires 10+ years of progressive, hands-on software engineering experience, including technical leadership of complex, production-scale systems and broad impact across multiple teams or product areas.
• Deep proficiency in one or more modern programming languages (Python, Java, C++, JavaScript, or TypeScript), with extensive experience in software architecture, debugging, automated testing, performance optimization, and maintainable code design.
• Demonstrated expertise in designing, building, deploying, and operating distributed software platforms across multiple layers of the application stack, including user-facing applications, APIs, backend services, data systems, workflow systems, and infrastructure.
• Strong knowledge of distributed systems, API design, data modeling, asynchronous processing, messaging, system integration, fault tolerance, security, reliability, and production operations.
• Experience deploying and operating production workloads in at least one major cloud platform (AWS, Microsoft Azure, or Google Cloud Platform), with practical knowledge of networking, compute, storage, identity, security, and managed services.
• Experience with containerized applications, Kubernetes or comparable orchestration platforms, CI/CD, infrastructure as code, configuration management, environment promotion, monitoring, and incident response.
• Experience designing secure multi-user systems, including identity and access management, authorization, secrets and credential management, workload isolation, audit logs, and operational controls.
• Experience integrating AI/ML services, LLM APIs, intelligent automation, or other nondeterministic components into production software systems. (Expertise in training foundation models is not required.)
• Exceptional written and verbal communication skills, with a proven ability to document and present technical designs, decisions, risks, tradeoffs, and roadmaps to technical and nontechnical stakeholders.
• Track record of independent, high-impact contributions improving product capabilities, engineering velocity, system reliability, platform reuse, or organizational effectiveness.

Qualifications

• Bachelor’s degree in Computer Engineering, Computer Science, Electrical Engineering, or a related technical field.
• A master’s degree in Computer Engineering, Computer Science, Data Science, Electrical Engineering, or a related technical field is preferred.

Work Environment

This job operates in a professional office environment and routinely uses standard office equipment.

Physical Demands

The physical demands described here are representative of those that must be met to successfully perform the essential functions of this job. The employee is regularly required to talk or hear, stand, walk, use hands to finger/handle/feel, and reach with hands and arms. Specific vision abilities required include close vision, distance vision, color vision, peripheral vision, depth perception, and the ability to adjust focus. This position requires the ability to occasionally lift office products and supplies up to 20 pounds.

Pay

USD 208,851.58 - 271,522.09 per year